The ability to group sensory stimuli into categories is crucial for efficient interaction with a
rich and ever-changing environment. In olfaction, basic features of categorical …

Reinforcement learning systems usually assume that a value function is defined over all
states (or state-action pairs) that can immediately give the value of a particular state or …

Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil
responses. For instance, the pupil dilates when we make decisions and these pupil size …

When a simple model-free strategy does not provide sufficient outcomes, an inference-
based strategy estimating a hidden task structure becomes essential for optimizing choices …

Many decision-making studies have demonstrated that humans learn either expected values
or relative preferences among choice options, yet little is known about what environmental …

In the original article, there was an error. In the abstract, the sentence “While VTE at the first
choice point increased with the number of repeated choices, VTE at the second choice point …

Studies of reinforcement learning in humans and animals have demonstrated a preference
for options that yielded relatively better outcomes in the past, even when those options are …

Perceptual learning is an enhancement in discriminability of similar stimuli following
experience with those stimuli. Here, we examined the efficacy of adding additional active …

Reinforcement learning algorithms have a long-standing success story in explaining the
dynamics of instrumental conditioning in humans and other species. While normative …

Human decisions can be reflexive or planned, being governed respectively by model-free
and model-based learning systems. These two systems might differ in their responsiveness …